Commercial deployment suggests an incremental path:
- Scenario Validation: Select high-value scenarios (e.g., customer service system) for POC testing and use the TMDB cases that come with the project to quickly verify feasibility
- Data preparation: Collect industry-specific tool API documentation and typical user query samples to customize the training base agent
- system integration: Interfacing the framework with existing enterprise systems through an API gateway, with Docker containerized deployment recommended at the initial stage
- Effectiveness Optimization: Analyze the execution trajectory using log_file.json to continuously improve the decision logic of each agent
The langchain and OpenAI integration that comes with the framework greatly reduces the deployment threshold, and can be completed in an average of 2-3 weeks from proof-of-concept to production environment online.
This answer comes from the articleCoAgents: a framework for learning to use tools through multi-intelligence collaborationThe
May not be reproduced without permission:AI productivity tools " How to rapidly deploy the CoAgents framework for commercialization?
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